deepwork_jobs
Creates and manages multi-step AI workflows. Use when defining, implementing, or improving DeepWork jobs.
Best use case
deepwork_jobs is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Creates and manages multi-step AI workflows. Use when defining, implementing, or improving DeepWork jobs.
Teams using deepwork_jobs should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/deepwork_jobs/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How deepwork_jobs Compares
| Feature / Agent | deepwork_jobs | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Creates and manages multi-step AI workflows. Use when defining, implementing, or improving DeepWork jobs.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# deepwork_jobs **Multi-step workflow**: Creates and manages multi-step AI workflows. Use when defining, implementing, or improving DeepWork jobs. > **CRITICAL**: Always invoke steps using the Skill tool. Never copy/paste step instructions directly. Core commands for managing DeepWork jobs. These commands help you define new multi-step workflows and learn from running them. The `define` command guides you through an interactive process to create a new job by asking structured questions about your workflow, understanding each step's inputs and outputs, and generating all necessary files. The `learn` command reflects on conversations where DeepWork jobs were run, identifies confusion or inefficiencies, and improves job instructions. It also captures bespoke learnings specific to the current run into AGENTS.md files in the working folder. ## Available Steps 1. **define** - Creates a job.yml specification by gathering workflow requirements through structured questions. Use when starting a new multi-step workflow. 2. **review_job_spec** - Reviews job.yml against quality criteria using a sub-agent for unbiased validation. Use after defining a job specification. (requires: define) 3. **implement** - Generates step instruction files and syncs slash commands from the job.yml specification. Use after job spec review passes. (requires: review_job_spec) 4. **learn** - Analyzes conversation history to improve job instructions and capture learnings. Use after running a job to refine it. ## Execution Instructions ### Step 1: Analyze Intent Parse any text following `/deepwork_jobs` to determine user intent: - "define" or related terms → start at `deepwork_jobs.define` - "review_job_spec" or related terms → start at `deepwork_jobs.review_job_spec` - "implement" or related terms → start at `deepwork_jobs.implement` - "learn" or related terms → start at `deepwork_jobs.learn` ### Step 2: Invoke Starting Step Use the Skill tool to invoke the identified starting step: ``` Skill tool: deepwork_jobs.define ``` ### Step 3: Continue Workflow Automatically After each step completes: 1. Check if there's a next step in the sequence 2. Invoke the next step using the Skill tool 3. Repeat until workflow is complete or user intervenes ### Handling Ambiguous Intent If user intent is unclear, use AskUserQuestion to clarify: - Present available steps as numbered options - Let user select the starting point ## Guardrails - Do NOT copy/paste step instructions directly; always use the Skill tool to invoke steps - Do NOT skip steps in the workflow unless the user explicitly requests it - Do NOT proceed to the next step if the current step's outputs are incomplete - Do NOT make assumptions about user intent; ask for clarification when ambiguous ## Context Files - Job definition: `.deepwork/jobs/deepwork_jobs/job.yml`
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